The data center energy crisis has been in the making for the past several decades, as data centers are designed primarily with peak performance and peak capacity in mind. With the doubling of transistor counts and performance in semiconductor devices at 18-month intervals following Moore's law, energy dissipation in servers have grown at an alarming rate. The smaller form factors of modern blade servers have, at the same time, permitted more and more servers to be packed into a given physical space, further worsening the already critical situation with server power dissipations within data centers. Adding to all of this is the trend to overprovision data center capacities and the use of overrated power supplies for the individual servers. Such over provisioning results in gross energy inefficiencies as servers and power supplies are generally designed to give very high energy efficiencies only at or near peak loading levels. The net result of all of these is that 50% and upwards of the total cost of ownership (TCO) for a data center is in the utility costs of operating and cooling the servers. From an economic standpoint, we spend about 2% of the nation's annual energy consumption on data centers. With electricity costs growing annually at about 7% to 10%, the situation is bleak and needs immediate correction with the use of innovative and dramatic solutions. The other benefits of operating energy-efficient data centers are of no less significance—reducing the carbon footprint and making the nation energy-secure are also worthy goals.
Traditional approaches to managing the data center energy crisis have been to use advanced cooling and packaging solutions, to use DC power sources for servers and a variety of other solutions at reducing the energy dissipation within servers. These latter solutions have included the use of dynamically changing the power-performance settings for individual server components, such as processors and hard disk drives, or on policy-based job scheduling that schedule the offered workload across servers to meet thermal objectives. The growing use of virtualization technologies in data center also supports flexible scheduling based energy management schemes. Virtually, all of these solutions are reactive in nature: energy management or cooling solutions are adjusted based on the feedback from sensors that sense temperature or some activity parameter (such as current computing load, performance metrics).